International Journal for Uncertainty Quantification
Выходит 6 номеров в год
ISSN Печать: 2152-5080
ISSN Онлайн: 2152-5099
IF:
1.7
5-Year IF:
1.9
Immediacy Index:
0.5
Eigenfactor:
0.0007
JCI:
0.5
SJR:
0.584
SNIP:
0.676
CiteScore™::
3
H-Index:
25
Indexed in
Том 6, 2016 Выпуск 1
DOI: 10.1615/Int.J.UncertaintyQuantification.v6.i1
GLOBAL SENSITIVITY ANALYSIS: AN EFFICIENT NUMERICAL METHOD FOR APPROXIMATING THE TOTAL SENSITIVITY INDEX
pp. 1-17
DOI: 10.1615/Int.J.UncertaintyQuantification.2016012354
AN EFFICIENT MESH-FREE IMPLICIT FILTER FOR NONLINEAR FILTERING PROBLEMS
pp. 19-33
DOI: 10.1615/Int.J.UncertaintyQuantification.2016013870
A METROPOLIS-HASTINGS METHOD FOR LINEAR INVERSE PROBLEMS WITH POISSON LIKELIHOOD AND GAUSSIAN PRIOR
pp. 35-55
DOI: 10.1615/Int.J.UncertaintyQuantification.2016013678
ROBUST UNCERTAINTY QUANTIFICATION USING PRECONDITIONED LEAST-SQUARES POLYNOMIAL APPROXIMATIONS WITH l1-REGULARIZATION
pp. 57-77
DOI: 10.1615/Int.J.UncertaintyQuantification.2016015915
REFINED LATINIZED STRATIFIED SAMPLING: A ROBUST SEQUENTIAL SAMPLE SIZE EXTENSION METHODOLOGY FOR HIGH-DIMENSIONAL LATIN HYPERCUBE AND STRATIFIED DESIGNS
pp. 79-97
DOI: 10.1615/Int.J.UncertaintyQuantification.2016011333
Последний выпуск
Статьи, принятые к публикации
EXTREME LEARNING MACHINES FOR VARIANCE-BASED GLOBAL SENSITIVITY ANALYSIS
Application of global sensitivity analysis for identification of probabilistic design spaces
Stochastic Galerkin method and port-Hamiltonian form for linear first-order ordinary differential equations
Analysis of the Challenges in Developing Sample-Based Multi-fidelity Estimators for Non-deterministic Models